Overview

Dataset statistics

Number of variables20
Number of observations193
Missing cells1691
Missing cells (%)43.8%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory30.5 KiB
Average record size in memory161.7 B

Variable types

Text5
Categorical6
Unsupported9

Dataset

Description광주광역시 북구 도로 굴착 현황으로 허가 번호, 동, 공사위치, 공사명, 신청자, 굴착개요, 공사방법, 복구방법, 복구주체, 공사기간, 굴착종류 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15084374/fileData.do

Alerts

Unnamed: 19 has constant value ""Constant
Dataset has 1 (0.5%) duplicate rowsDuplicates
Unnamed: 15 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
Unnamed: 14 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
Unnamed: 16 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
Unnamed: 18 is highly overall correlated with Unnamed: 5 and 3 other fieldsHigh correlation
Unnamed: 1 is highly overall correlated with Unnamed: 14 and 2 other fieldsHigh correlation
Unnamed: 5 is highly overall correlated with Unnamed: 14 and 3 other fieldsHigh correlation
2 0 2 2 년 도 로 굴 착 및 점 용 허 가 대 장 has 98 (50.8%) missing valuesMissing
Unnamed: 2 has 98 (50.8%) missing valuesMissing
Unnamed: 3 has 193 (100.0%) missing valuesMissing
Unnamed: 4 has 98 (50.8%) missing valuesMissing
Unnamed: 7 has 28 (14.5%) missing valuesMissing
Unnamed: 8 has 172 (89.1%) missing valuesMissing
Unnamed: 9 has 178 (92.2%) missing valuesMissing
Unnamed: 10 has 83 (43.0%) missing valuesMissing
Unnamed: 11 has 129 (66.8%) missing valuesMissing
Unnamed: 12 has 181 (93.8%) missing valuesMissing
Unnamed: 13 has 142 (73.6%) missing valuesMissing
Unnamed: 17 has 98 (50.8%) missing valuesMissing
Unnamed: 19 has 192 (99.5%) missing valuesMissing
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 21:30:13.322598
Analysis finished2023-12-12 21:30:15.276024
Duration1.95 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2 0 2 2 년 도 로 굴 착 및 점 용 허 가 대 장
Text

MISSING 

Distinct95
Distinct (%)100.0%
Missing98
Missing (%)50.8%
Memory size1.6 KiB
2023-12-13T06:30:15.504947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9052632
Min length4

Characters and Unicode

Total characters466
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)100.0%

Sample

1st row허가번호
2nd row22-1
3rd row22-2
4th row22-3
5th row22-4
ValueCountFrequency (%)
허가번호 1
 
1.1%
22-71 1
 
1.1%
22-70 1
 
1.1%
22-69 1
 
1.1%
22-68 1
 
1.1%
22-67 1
 
1.1%
22-66 1
 
1.1%
22-65 1
 
1.1%
22-64 1
 
1.1%
22-63 1
 
1.1%
Other values (85) 85
89.5%
2023-12-13T06:30:15.912444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 208
44.6%
- 94
20.2%
1 20
 
4.3%
3 20
 
4.3%
4 20
 
4.3%
5 20
 
4.3%
6 19
 
4.1%
7 19
 
4.1%
8 18
 
3.9%
9 15
 
3.2%
Other values (5) 13
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 368
79.0%
Dash Punctuation 94
 
20.2%
Other Letter 4
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 208
56.5%
1 20
 
5.4%
3 20
 
5.4%
4 20
 
5.4%
5 20
 
5.4%
6 19
 
5.2%
7 19
 
5.2%
8 18
 
4.9%
9 15
 
4.1%
0 9
 
2.4%
Other Letter
ValueCountFrequency (%)
허 1
25.0%
가 1
25.0%
번 1
25.0%
호 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 462
99.1%
Hangul 4
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 208
45.0%
- 94
20.3%
1 20
 
4.3%
3 20
 
4.3%
4 20
 
4.3%
5 20
 
4.3%
6 19
 
4.1%
7 19
 
4.1%
8 18
 
3.9%
9 15
 
3.2%
Hangul
ValueCountFrequency (%)
허 1
25.0%
가 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 462
99.1%
Hangul 4
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 208
45.0%
- 94
20.3%
1 20
 
4.3%
3 20
 
4.3%
4 20
 
4.3%
5 20
 
4.3%
6 19
 
4.1%
7 19
 
4.1%
8 18
 
3.9%
9 15
 
3.2%
Hangul
ValueCountFrequency (%)
허 1
25.0%
가 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
94 
일곡동
 
9
각화동
 
8
풍향동
 
7
양산동
 
7
Other values (27)
68 

Length

Max length8
Median length5
Mean length3.5181347
Min length1

Unique

Unique12 ?
Unique (%)6.2%

Sample

1st row<NA>
2nd row동
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 94
48.7%
일곡동 9
 
4.7%
각화동 8
 
4.1%
풍향동 7
 
3.6%
양산동 7
 
3.6%
연제동 6
 
3.1%
오룡동 5
 
2.6%
신안동 5
 
2.6%
월출동 5
 
2.6%
중흥동 5
 
2.6%
Other values (22) 42
21.8%

Length

2023-12-13T06:30:16.045404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 94
48.7%
일곡동 9
 
4.7%
각화동 8
 
4.1%
풍향동 7
 
3.6%
양산동 7
 
3.6%
연제동 6
 
3.1%
월출동 5
 
2.6%
중흥동 5
 
2.6%
신안동 5
 
2.6%
오룡동 5
 
2.6%
Other values (22) 42
21.8%

Unnamed: 2
Text

MISSING 

Distinct90
Distinct (%)94.7%
Missing98
Missing (%)50.8%
Memory size1.6 KiB
2023-12-13T06:30:16.289801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length14.263158
Min length3

Characters and Unicode

Total characters1355
Distinct characters105
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)89.5%

Sample

1st row공 사 위 치
2nd row본촌동762-15~ 지야동 804-27
3rd row오치동 957-12번지 일원
4th row운암동 모아아파트(228)
5th row동림동 233번지 일원
ValueCountFrequency (%)
일원 61
 
19.7%
등 22
 
7.1%
각화동 8
 
2.6%
주변 7
 
2.3%
풍향동 7
 
2.3%
일곡동 6
 
1.9%
연제동 6
 
1.9%
양산동 6
 
1.9%
2개소 5
 
1.6%
오룡동 5
 
1.6%
Other values (133) 177
57.1%
2023-12-13T06:30:16.717639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
204
 
15.1%
동 93
 
6.9%
1 84
 
6.2%
일 80
 
5.9%
원 69
 
5.1%
- 59
 
4.4%
2 48
 
3.5%
지 46
 
3.4%
8 45
 
3.3%
번 43
 
3.2%
Other values (95) 584
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 666
49.2%
Decimal Number 391
28.9%
Space Separator 204
 
15.1%
Dash Punctuation 59
 
4.4%
Control 16
 
1.2%
Math Symbol 8
 
0.6%
Other Punctuation 4
 
0.3%
Uppercase Letter 3
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 93
14.0%
일 80
 
12.0%
원 69
 
10.4%
지 46
 
6.9%
번 43
 
6.5%
소 26
 
3.9%
개 26
 
3.9%
등 26
 
3.9%
각 13
 
2.0%
산 12
 
1.8%
Other values (75) 232
34.8%
Decimal Number
ValueCountFrequency (%)
1 84
21.5%
2 48
12.3%
8 45
11.5%
5 37
9.5%
0 34
8.7%
6 32
 
8.2%
9 29
 
7.4%
4 29
 
7.4%
7 28
 
7.2%
3 25
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
K 1
33.3%
J 1
33.3%
Space Separator
ValueCountFrequency (%)
204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Control
ValueCountFrequency (%)
16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 686
50.6%
Hangul 666
49.2%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 93
14.0%
일 80
 
12.0%
원 69
 
10.4%
지 46
 
6.9%
번 43
 
6.5%
소 26
 
3.9%
개 26
 
3.9%
등 26
 
3.9%
각 13
 
2.0%
산 12
 
1.8%
Other values (75) 232
34.8%
Common
ValueCountFrequency (%)
204
29.7%
1 84
12.2%
- 59
 
8.6%
2 48
 
7.0%
8 45
 
6.6%
5 37
 
5.4%
0 34
 
5.0%
6 32
 
4.7%
9 29
 
4.2%
4 29
 
4.2%
Other values (7) 85
12.4%
Latin
ValueCountFrequency (%)
S 1
33.3%
K 1
33.3%
J 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 689
50.8%
Hangul 666
49.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
204
29.6%
1 84
12.2%
- 59
 
8.6%
2 48
 
7.0%
8 45
 
6.5%
5 37
 
5.4%
0 34
 
4.9%
6 32
 
4.6%
9 29
 
4.2%
4 29
 
4.2%
Other values (10) 88
12.8%
Hangul
ValueCountFrequency (%)
동 93
14.0%
일 80
 
12.0%
원 69
 
10.4%
지 46
 
6.9%
번 43
 
6.5%
소 26
 
3.9%
개 26
 
3.9%
등 26
 
3.9%
각 13
 
2.0%
산 12
 
1.8%
Other values (75) 232
34.8%

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

Unnamed: 4
Text

MISSING 

Distinct92
Distinct (%)96.8%
Missing98
Missing (%)50.8%
Memory size1.6 KiB
2023-12-13T06:30:17.023567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length27.494737
Min length5

Characters and Unicode

Total characters2612
Distinct characters182
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)93.7%

Sample

1st row공 사 명
2nd row본촌동762-15~ 지야동 804-27 등 8개소 도시가스 배관 매설 및 철거공사
3rd row오치동 957-12번지 일원 지중관로 매설공사
4th row운암동 모아아파트(228) 저압 등 2개소 도시가스 배관 매설 및 철거공사
5th row동림동 233번지 일원 상수관로 매설공사
ValueCountFrequency (%)
일원 57
 
9.5%
매설공사 37
 
6.2%
등 33
 
5.5%
매설 31
 
5.2%
및 24
 
4.0%
도시가스 21
 
3.5%
배관 21
 
3.5%
통신관로 15
 
2.5%
철거 12
 
2.0%
주변 9
 
1.5%
Other values (196) 338
56.5%
2023-12-13T06:30:17.500031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
458
 
17.5%
일 83
 
3.2%
동 80
 
3.1%
1 77
 
2.9%
관 76
 
2.9%
사 75
 
2.9%
설 74
 
2.8%
매 72
 
2.8%
공 71
 
2.7%
지 63
 
2.4%
Other values (172) 1483
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1625
62.2%
Space Separator 458
 
17.5%
Decimal Number 357
 
13.7%
Dash Punctuation 56
 
2.1%
Control 51
 
2.0%
Uppercase Letter 15
 
0.6%
Open Punctuation 14
 
0.5%
Close Punctuation 14
 
0.5%
Other Punctuation 11
 
0.4%
Lowercase Letter 10
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 83
 
5.1%
동 80
 
4.9%
관 76
 
4.7%
사 75
 
4.6%
설 74
 
4.6%
매 72
 
4.4%
공 71
 
4.4%
지 63
 
3.9%
원 63
 
3.9%
로 52
 
3.2%
Other values (147) 916
56.4%
Decimal Number
ValueCountFrequency (%)
1 77
21.6%
2 41
11.5%
5 39
10.9%
8 35
9.8%
0 31
8.7%
7 31
8.7%
9 28
 
7.8%
4 26
 
7.3%
6 25
 
7.0%
3 24
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
T 6
40.0%
L 6
40.0%
S 1
 
6.7%
J 1
 
6.7%
K 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
/ 6
54.5%
, 5
45.5%
Lowercase Letter
ValueCountFrequency (%)
v 5
50.0%
k 5
50.0%
Space Separator
ValueCountFrequency (%)
458
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Control
ValueCountFrequency (%)
51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1625
62.2%
Common 962
36.8%
Latin 25
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 83
 
5.1%
동 80
 
4.9%
관 76
 
4.7%
사 75
 
4.6%
설 74
 
4.6%
매 72
 
4.4%
공 71
 
4.4%
지 63
 
3.9%
원 63
 
3.9%
로 52
 
3.2%
Other values (147) 916
56.4%
Common
ValueCountFrequency (%)
458
47.6%
1 77
 
8.0%
- 56
 
5.8%
51
 
5.3%
2 41
 
4.3%
5 39
 
4.1%
8 35
 
3.6%
0 31
 
3.2%
7 31
 
3.2%
9 28
 
2.9%
Other values (8) 115
 
12.0%
Latin
ValueCountFrequency (%)
T 6
24.0%
L 6
24.0%
v 5
20.0%
k 5
20.0%
S 1
 
4.0%
J 1
 
4.0%
K 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1625
62.2%
ASCII 987
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
458
46.4%
1 77
 
7.8%
- 56
 
5.7%
51
 
5.2%
2 41
 
4.2%
5 39
 
4.0%
8 35
 
3.5%
0 31
 
3.1%
7 31
 
3.1%
9 28
 
2.8%
Other values (15) 140
 
14.2%
Hangul
ValueCountFrequency (%)
일 83
 
5.1%
동 80
 
4.9%
관 76
 
4.7%
사 75
 
4.6%
설 74
 
4.6%
매 72
 
4.4%
공 71
 
4.4%
지 63
 
3.9%
원 63
 
3.9%
로 52
 
3.2%
Other values (147) 916
56.4%

Unnamed: 5
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
98 
해양에너지㈜
26 
한국전력공사
19 
(주)LG유플러스
 
6
상수도사업본부 동북수도사업소
 
5
Other values (25)
39 

Length

Max length32
Median length4
Mean length5.8860104
Min length3

Unique

Unique17 ?
Unique (%)8.8%

Sample

1st row<NA>
2nd row신청자
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 98
50.8%
해양에너지㈜ 26
 
13.5%
한국전력공사 19
 
9.8%
(주)LG유플러스 6
 
3.1%
상수도사업본부 동북수도사업소 5
 
2.6%
엘지유플러스 3
 
1.6%
㈜리채 3
 
1.6%
광주중외공원개발㈜ 3
 
1.6%
㈜엘지유플러스 에스케이텔레콤 3
 
1.6%
에스케이텔레콤㈜ 3
 
1.6%
Other values (20) 24
 
12.4%

Length

2023-12-13T06:30:17.649135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 98
47.1%
해양에너지㈜ 26
 
12.5%
한국전력공사 19
 
9.1%
주)lg유플러스 8
 
3.8%
상수도사업본부 6
 
2.9%
㈜엘지유플러스 6
 
2.9%
동북수도사업소 5
 
2.4%
엘지유플러스 4
 
1.9%
㈜리채 3
 
1.4%
광주중외공원개발㈜ 3
 
1.4%
Other values (23) 30
 
14.4%

Unnamed: 6
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.5%
Memory size1.6 KiB

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)14.5%
Memory size1.6 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing172
Missing (%)89.1%
Memory size1.6 KiB

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing178
Missing (%)92.2%
Memory size1.6 KiB

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing83
Missing (%)43.0%
Memory size1.6 KiB

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing129
Missing (%)66.8%
Memory size1.6 KiB

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing181
Missing (%)93.8%
Memory size1.6 KiB

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing142
Missing (%)73.6%
Memory size1.6 KiB

Unnamed: 14
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
98 
노면 개착 시공
94 
공사방법
 
1

Length

Max length8
Median length4
Mean length5.9481865
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row공사방법
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 98
50.8%
노면 개착 시공 94
48.7%
공사방법 1
 
0.5%

Length

2023-12-13T06:30:17.787732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:30:17.903657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
25.7%
노면 94
24.7%
개착 94
24.7%
시공 94
24.7%
공사방법 1
 
0.3%

Unnamed: 15
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
98 
기계절삭포장
94 
복구방법
 
1

Length

Max length6
Median length4
Mean length4.9740933
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row복구방법
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 98
50.8%
기계절삭포장 94
48.7%
복구방법 1
 
0.5%

Length

2023-12-13T06:30:18.024274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:30:18.152553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
50.8%
기계절삭포장 94
48.7%
복구방법 1
 
0.5%

Unnamed: 16
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
98 
원인자
94 
복구 주체
 
1

Length

Max length5
Median length4
Mean length3.5181347
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row복구 주체
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 98
50.8%
원인자 94
48.7%
복구 주체 1
 
0.5%

Length

2023-12-13T06:30:18.269029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:30:18.376224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
50.5%
원인자 94
48.5%
복구 1
 
0.5%
주체 1
 
0.5%

Unnamed: 17
Text

MISSING 

Distinct61
Distinct (%)64.2%
Missing98
Missing (%)50.8%
Memory size1.6 KiB
2023-12-13T06:30:18.586878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length19.557895
Min length4

Characters and Unicode

Total characters1858
Distinct characters27
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)45.3%

Sample

1st row공사기간
2nd row2022.1. (착공일로부터 3일~20일)
3rd row2022.1. (착공일로부터 5일)
4th row2022.1. (착공일로부터 3일)
5th row2022.1. (착공일로부터 30일)
ValueCountFrequency (%)
착공일로부터 83
29.9%
3일 39
14.0%
2022.4 12
 
4.3%
2022.11 10
 
3.6%
2022.6 9
 
3.2%
5일 8
 
2.9%
2022.3 8
 
2.9%
2022.9 8
 
2.9%
2022.5 7
 
2.5%
2022.12 7
 
2.5%
Other values (46) 87
31.3%
2023-12-13T06:30:18.955595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 312
16.8%
. 218
11.7%
일 167
 
9.0%
0 127
 
6.8%
94
 
5.1%
89
 
4.8%
) 85
 
4.6%
( 85
 
4.6%
공 84
 
4.5%
착 83
 
4.5%
Other values (17) 514
27.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 677
36.4%
Other Letter 590
31.8%
Other Punctuation 218
 
11.7%
Space Separator 94
 
5.1%
Control 89
 
4.8%
Close Punctuation 85
 
4.6%
Open Punctuation 85
 
4.6%
Math Symbol 20
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 167
28.3%
공 84
14.2%
착 83
14.1%
로 83
14.1%
부 83
14.1%
터 83
14.1%
개 2
 
0.3%
월 2
 
0.3%
사 1
 
0.2%
기 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 312
46.1%
0 127
18.8%
1 81
 
12.0%
3 69
 
10.2%
5 25
 
3.7%
4 17
 
2.5%
6 15
 
2.2%
7 14
 
2.1%
9 10
 
1.5%
8 7
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 218
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%
Control
ValueCountFrequency (%)
89
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1268
68.2%
Hangul 590
31.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 312
24.6%
. 218
17.2%
0 127
10.0%
94
 
7.4%
89
 
7.0%
) 85
 
6.7%
( 85
 
6.7%
1 81
 
6.4%
3 69
 
5.4%
5 25
 
2.0%
Other values (6) 83
 
6.5%
Hangul
ValueCountFrequency (%)
일 167
28.3%
공 84
14.2%
착 83
14.1%
로 83
14.1%
부 83
14.1%
터 83
14.1%
개 2
 
0.3%
월 2
 
0.3%
사 1
 
0.2%
기 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1268
68.2%
Hangul 590
31.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 312
24.6%
. 218
17.2%
0 127
10.0%
94
 
7.4%
89
 
7.0%
) 85
 
6.7%
( 85
 
6.7%
1 81
 
6.4%
3 69
 
5.4%
5 25
 
2.0%
Other values (6) 83
 
6.5%
Hangul
ValueCountFrequency (%)
일 167
28.3%
공 84
14.2%
착 83
14.1%
로 83
14.1%
부 83
14.1%
터 83
14.1%
개 2
 
0.3%
월 2
 
0.3%
사 1
 
0.2%
기 1
 
0.2%

Unnamed: 18
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
98 
가스관
26 
통신관
25 
전선관
24 
상수관
 
5
Other values (6)
15 

Length

Max length5
Median length4
Mean length3.5647668
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row굴착종류
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 98
50.8%
가스관 26
 
13.5%
통신관 25
 
13.0%
전선관 24
 
12.4%
상수관 5
 
2.6%
전기통신관 4
 
2.1%
수도관 3
 
1.6%
우수관 3
 
1.6%
하수관 2
 
1.0%
접합확인 2
 
1.0%

Length

2023-12-13T06:30:19.133239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 98
50.8%
가스관 26
 
13.5%
통신관 25
 
13.0%
전선관 24
 
12.4%
상수관 5
 
2.6%
전기통신관 4
 
2.1%
수도관 3
 
1.6%
우수관 3
 
1.6%
하수관 2
 
1.0%
접합확인 2
 
1.0%

Unnamed: 19
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing192
Missing (%)99.5%
Memory size1.6 KiB
2023-12-13T06:30:19.233835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row비고
ValueCountFrequency (%)
비고 1
100.0%
2023-12-13T06:30:19.477806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Correlations

2023-12-13T06:30:19.593506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2 0 2 2 년 도 로 굴 착 및 점 용 허 가 대 장Unnamed: 1Unnamed: 2Unnamed: 4Unnamed: 5Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18
2 0 2 2 년 도 로 굴 착 및 점 용 허 가 대 장1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0000.9281.0001.0001.0000.9160.870
Unnamed: 21.0001.0001.0001.0000.9981.0001.0001.0000.5700.984
Unnamed: 41.0001.0001.0001.0001.0001.0001.0001.0000.0001.000
Unnamed: 51.0000.9280.9981.0001.0001.0001.0001.0000.9420.979
Unnamed: 141.0001.0001.0001.0001.0001.0000.6920.6921.0001.000
Unnamed: 151.0001.0001.0001.0001.0000.6921.0000.6921.0001.000
Unnamed: 161.0001.0001.0001.0001.0000.6920.6921.0001.0001.000
Unnamed: 171.0000.9160.5700.0000.9421.0001.0001.0001.0000.949
Unnamed: 181.0000.8700.9841.0000.9791.0001.0001.0000.9491.000
2023-12-13T06:30:19.740836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 15Unnamed: 14Unnamed: 5Unnamed: 16Unnamed: 1Unnamed: 18
Unnamed: 151.0000.4860.8420.4860.8420.956
Unnamed: 140.4861.0000.8420.4860.8420.956
Unnamed: 50.8420.8421.0000.8420.3930.754
Unnamed: 160.4860.4860.8421.0000.8420.956
Unnamed: 10.8420.8420.3930.8421.0000.473
Unnamed: 180.9560.9560.7540.9560.4731.000
2023-12-13T06:30:19.851293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 5Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 18
Unnamed: 11.0000.3930.8420.8420.8420.473
Unnamed: 50.3931.0000.8420.8420.8420.754
Unnamed: 140.8420.8421.0000.4860.4860.956
Unnamed: 150.8420.8420.4861.0000.4860.956
Unnamed: 160.8420.8420.4860.4861.0000.956
Unnamed: 180.4730.7540.9560.9560.9561.000

Missing values

2023-12-13T06:30:14.518930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:30:14.765638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-13T06:30:15.033707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

2 0 2 2 년 도 로 굴 착 및 점 용 허 가 대 장Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
0<NA><NA><NA><NA><NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN<NA><NA><NA><NA><NA><NA>
1허가번호동공 사 위 치<NA>공 사 명신청자굴 착 개 요NaNNaNNaNNaNNaNNaNNaN공사방법복구방법복구 주체공사기간굴착종류비고
2<NA><NA><NA><NA><NA><NA>계차도(아스콘)차도(콘크리트)보도(콘크리트)보도(고압블럭)보도(투수콘)압입기타\n(사리도 등)<NA><NA><NA><NA><NA><NA>
3<NA><NA><NA><NA><NA><NA>34723.27 (연장m)27759.1783.2505591.66774.990464.25<NA><NA><NA><NA><NA><NA>
4<NA><NA><NA><NA><NA><NA>85698.54 (면적㎡)69411.17157.769013470.471544.6701024.47<NA><NA><NA><NA><NA><NA>
522-1본촌동본촌동762-15~ 지야동 804-27<NA>본촌동762-15~ 지야동 804-27 등 8개소 도시가스 배관 매설 및 철거공사해양에너지㈜61332NaNNaNNaN00581노면 개착 시공기계절삭포장원인자2022.1. (착공일로부터 3일~20일)가스관<NA>
6<NA>지야동<NA><NA><NA><NA>735.638.4NaNNaNNaN0NaN697.2<NA><NA><NA><NA><NA><NA>
722-2오치동오치동 957-12번지 일원<NA>오치동 957-12번지 일원 지중관로 매설공사한국전력공사4NaNNaNNaNNaN40NaN노면 개착 시공기계절삭포장원인자2022.1. (착공일로부터 5일)전선관<NA>
8<NA><NA><NA><NA><NA><NA>4.8NaNNaNNaNNaN4.8NaNNaN<NA><NA><NA><NA><NA><NA>
922-3운암동운암동 모아아파트(228)<NA>운암동 모아아파트(228) 저압 등 2개소 도시가스 배관 매설 및 철거공사해양에너지㈜114NaN03004노면 개착 시공기계절삭포장원인자2022.1. (착공일로부터 3일)가스관<NA>
2 0 2 2 년 도 로 굴 착 및 점 용 허 가 대 장Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
18322-91두암동두암동 909번지 일원<NA>두암동 909번지 일원 통신관로 매설공사엘지유플러스6NaNNaNNaN6NaNNaNNaN노면 개착 시공기계절삭포장원인자2022.12. (착공일로부터 3일)통신관<NA>
184<NA><NA><NA><NA><NA><NA>7.2NaNNaNNaN7.2NaNNaNNaN<NA><NA><NA><NA><NA><NA>
18522-92월출동월출동 965-1번지 일원<NA>월출동 965-1번지 일원 파형관 매설공사한국전력공사21.6NaNNaNNaN21.6NaNNaNNaN노면 개착 시공기계절삭포장원인자2022.12. (착공일로부터 5일)전선관<NA>
186<NA><NA><NA><NA><NA><NA>14.05NaNNaNNaN14.05NaNNaNNaN<NA><NA><NA><NA><NA><NA>
18722-93임동임동 620-1번지 일원<NA>임동 620-1번지 일원 지중관로 매설한국전력공사15NaNNaNNaN15NaNNaNNaN노면 개착 시공기계절삭포장원인자2022.12. (착공일로부터 15일)전선관<NA>
188<NA><NA><NA><NA><NA><NA>15.9NaNNaNNaN15.9NaNNaNNaN<NA><NA><NA><NA><NA><NA>
18922-94각화동각화동 94-4번지 주변<NA>각화동 94-4번지 주변 등 7개소 광주천환경정비 관로접합확인 공사㈜리채2121NaNNaNNaNNaNNaNNaN노면 개착 시공기계절삭포장원인자22.11.3.~23.1.15.접합확인<NA>
190<NA><NA><NA><NA><NA><NA>4242NaNNaNNaNNaNNaNNaN<NA><NA><NA><NA><NA><NA>
19122-95우치로북구 우치로 일원<NA>용전천 개수공사광주광역시종합건설본부644644NaNNaNNaNNaNNaNNaN노면 개착 시공기계절삭포장원인자22.5.7.~23.12.31.하수관<NA>
192<NA><NA><NA><NA><NA><NA>42104210NaNNaNNaNNaNNaNNaN<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

2 0 2 2 년 도 로 굴 착 및 점 용 허 가 대 장Unnamed: 1Unnamed: 2Unnamed: 4Unnamed: 5Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>94